WO2019174282A1 - 房车供电控制方法和装置 - Google Patents

房车供电控制方法和装置 Download PDF

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Publication number
WO2019174282A1
WO2019174282A1 PCT/CN2018/114453 CN2018114453W WO2019174282A1 WO 2019174282 A1 WO2019174282 A1 WO 2019174282A1 CN 2018114453 W CN2018114453 W CN 2018114453W WO 2019174282 A1 WO2019174282 A1 WO 2019174282A1
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WIPO (PCT)
Prior art keywords
appliance
power
data
power supply
target
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PCT/CN2018/114453
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English (en)
French (fr)
Inventor
谌进
宋德超
陈翀
Original Assignee
格力电器（武汉）有限公司
珠海格力电器股份有限公司
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Publication of WO2019174282A1 publication Critical patent/WO2019174282A1/zh

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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J1/00—Circuit arrangements for dc mains or dc distribution networks
    • H02J1/08—Three-wire systems; Systems having more than three wires
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J1/00—Circuit arrangements for dc mains or dc distribution networks
    • H02J1/10—Parallel operation of dc sources
    • H02J1/106—Parallel operation of dc sources for load balancing, symmetrisation, or sharing
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/34—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering
    • H02J7/35—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering with light sensitive cells
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
    • H04L12/2803—Home automation networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
    • H04L12/2803—Home automation networks
    • H04L12/2816—Controlling appliance services of a home automation network by calling their functionalities
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/10—The network having a local or delimited stationary reach
    • H02J2310/12—The local stationary network supplying a household or a building
    • H02J2310/14—The load or loads being home appliances
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/40—The network being an on-board power network, i.e. within a vehicle

Definitions

  • the present application relates to the field of motor vehicles, and in particular to a method and device for controlling power supply of a motor home.
  • the RV is popular among consumers because it is equipped with kitchen, bathroom, air conditioner, TV, bedroom and other complete equipment.
  • the power management system is an extremely urgent problem to be solved.
  • the existing power supply schemes for RVs usually include battery power supply, solar panel power supply, mechanical motion storage, and power supply.
  • battery power supply due to limited storage capacity of the RV, how to uniformly dispatch and manage the internal power supply system of the RV and maximize consumption.
  • the demand for normal living electricity has always been a big problem.
  • the main purpose of the present application is to provide a method and device for controlling power supply of a motor home to solve the problem of power supply control of the motor home.
  • a method for controlling power supply of a motor home comprising: acquiring current power data of the motor home; determining power to be adjusted according to the current power data and a pre-trained power control model a target electrical appliance of the state; controlling a power supply state of the target electrical appliance, wherein controlling the power supply state of the target electrical appliance includes powering the target electrical appliance, powering down the target electrical appliance, or adjusting an operating state of the target electrical appliance.
  • the method further includes: acquiring sample data, wherein the sample data includes at least each of the vehicle interiors The power consumption data of the electric appliance and the operation data of the user for each electric appliance; the sample data is divided into training sample data and test sample data; the training sample data is model-trained to obtain a power control model; and the test sample is passed The data is tested on the power control model to obtain a test result; and the power control model is used as the pre-trained power control model if the test result meets a preset condition.
  • acquiring the sample data includes: acquiring a power-on time period of each appliance; acquiring a usage time period of each appliance; acquiring energy consumption of each appliance; and acquiring user operation data of each appliance.
  • acquiring the sample data includes: generating corresponding identification information according to the device identification number and the physical address of each appliance; and acquiring power supply data of each appliance according to the identifier information.
  • the user's operation data for each appliance includes: operation data of each appliance by the user through the mobile terminal and operation data directly by the user for each appliance.
  • the training sample data is subjected to model training, and the power control model is obtained by: using the influence parameter of the power consumption state of the trainer in the training sample data as an input parameter of the model; and the power supply state of each electric appliance based on the electric power of the motorhome
  • the adjustment data is used as an output parameter; the model is trained by the input parameter and the output parameter to obtain the power control model.
  • the power control model includes a neural network model
  • the training sample data is model-trained to obtain a power control model, including: according to each appliance's power on/off time period, usage time period, use energy consumption, and user operation data. Determining the network structure of the neural network model, the number of input nodes of the network, the number of output nodes of the network, the number of network hidden layers, the number of network index nodes, and the initial weight of the network.
  • the method further includes: receiving a control instruction of the user on the first appliance in the motorhome; and controlling an operation state of the first appliance according to the control instruction.
  • the method further includes: acquiring a permission level of the user; determining whether the permission level of the user allows the first appliance The operating state is adjusted; if allowed, the operating state of the first electrical appliance is adjusted; if not allowed, the operating state of the first electrical appliance is not adjusted.
  • the method further includes: determining a power supply state of the target appliance according to the permission level of the user.
  • the method further includes: determining whether the current remaining power of the motorhome is less than a preset threshold; and displaying navigation information when the remaining power of the motorhome is less than a preset threshold, wherein The navigation information is a navigation route from a current location of the RV to a nearest charging location.
  • the remote server determines, according to the current power data and the pre-trained power control model, the target appliance to be adjusted to the power supply state.
  • a motor home power supply control device comprising: an acquisition unit configured to acquire current power consumption data of the motor home; and a determining unit configured to be based on the current power amount Data and a pre-trained power control model determine a target appliance to be adjusted in a power supply state; a control unit configured to control a power supply state of the target appliance, wherein controlling a power state of the target appliance includes powering the target appliance, The target appliance is powered off or adjusts an operating state of the target appliance.
  • a storage medium including a stored program, wherein, when the program is running, the device in which the storage medium is located is executed to perform the power supply control of the RV according to the present application. method.
  • a processor for running a program, wherein the program is executed to execute the RV power supply control method of the present application.
  • the present application obtains the current electric quantity data of the RV; determines the target electric appliance to be adjusted according to the current electric quantity data and the pre-trained electric quantity control model; and controls the power supply status of the target electric appliance, wherein controlling the power supply status of the target electric appliance includes the target electric appliance Power supply, power off the target electrical appliance or adjust the operating state of the target electrical appliance, solves the problem that the power management method in the motor vehicle is not intelligent, and thus achieves the effect of improving the intelligence of the power management in the passenger car.
  • FIG. 1 is a flowchart of a method for controlling power supply of a motor home according to an embodiment of the present application
  • FIG. 2 is a schematic diagram of interaction between a user's internal power equipment and a user according to an embodiment of the present application
  • FIG. 3 is a schematic diagram of a neural network algorithm for power distribution of a power supply system of a motor home according to an embodiment of the present application
  • FIG. 4 is a flow chart of a neural network algorithm in accordance with an embodiment of the present application.
  • FIG. 5 is a schematic diagram of a motor home power supply control device according to an embodiment of the present application.
  • the embodiment of the present application provides a method for controlling power supply of a motor home.
  • FIG. 1 is a flowchart of a method for controlling power supply of a motor home according to an embodiment of the present application. As shown in FIG. 1 , the method includes the following steps:
  • Step S102 Acquire current electric quantity data of the RV
  • Step S104 determining, according to current power data and a pre-trained power control model, a target appliance to be adjusted in a power supply state;
  • Step S106 Control a power supply state of the target appliance, wherein controlling the power state of the target appliance includes powering the target appliance, powering off the target appliance, or adjusting an operating state of the target appliance.
  • the embodiment adopts acquiring the current electric quantity data of the motor home; determining the target electric appliance to be adjusted according to the current electric quantity data and the pre-trained electric quantity control model; controlling the power supply status of the target electric appliance, wherein controlling the power supply status of the target electric appliance includes the target
  • controlling the power supply status of the target electric appliance includes the target
  • the power supply of the electric appliance, the power failure of the target electric appliance or the adjustment of the operating state of the target electric appliance solves the problem that the electric power management method in the electric vehicle is not intelligent, thereby achieving the effect of improving the intelligence of the electric power management in the electric vehicle.
  • the current electric quantity data of the RV may be the current remaining electric quantity of the RV, and may also include the current electric energy consumption data of the RV.
  • the pre-trained model may be the electric quantity of all the electric appliances in the RV based on the specific conditions of the RV.
  • the consumption model includes the power consumption of different time periods. Because the consumers use different electrical appliances in different time periods, the power consumption of the RV is different in different time periods.
  • the pre-trained model and the current electricity data can determine the current
  • the best power supply strategy for power data includes which appliances are supplied, which appliances are not powered, or which controls the operating status of some appliances. For example, water heaters are generally used around 10 pm and are not currently used. If the current car is not enough, the water heater can be suspended.
  • Heating, or suspending the use of air conditioners, adjusting the air conditioning operation mode to save power, etc. after determining the target appliance that needs to adjust the power supply status, it can control the power supply status of the target appliance so that the current power consumption of the motor home can be optimally utilized, so that the utility vehicle can be used internally. Electrical management is more intelligent .
  • sample data where the sample data includes at least power consumption data of each appliance in the passenger car and the user pair The operation data of the electrical appliance; the sample data is divided into the training sample data and the test sample data; the training sample data is trained by the model to obtain the power control model; the power control model is tested by the test sample data to obtain the test result; When the preset conditions are met, the power control model is used as a pre-trained power control model.
  • the sample data can be collected based on the operation of the specific RV. For example, the usage and power consumption of the electric appliances in the RV at 24 time points of the day are collected, and the operation control data of the user for each electric appliance is collected, and the sample data can be It is divided into training sample data and test sample data.
  • the model is trained based on the training sample data, and then the model is tested using the test data until the preset condition is met before the trained model is used as a pre-trained power control model.
  • the preset condition may be that the numerical error is less than a certain threshold.
  • obtaining the sample data includes: obtaining a power-on time period of each electrical appliance; obtaining a usage time period of each electrical appliance; obtaining an energy consumption of each electrical appliance; and acquiring user operation data of each electrical appliance.
  • the sample data can be more comprehensive electrical usage data, for example, the time of the switch, the energy consumption data during use, the operation data of the user using the electrical appliance, etc. In general, the more data obtained, the more comprehensive, the more Conducive to the establishment of accurate models.
  • the obtaining the sample data includes: generating corresponding identification information according to the device identification number and the physical address of each appliance; and acquiring power supply data of each appliance according to the identifier information.
  • unique identification information can be generated for each appliance, and the generation of the identification information can be based on the identity number (mid) and physical address of each appliance.
  • the operation data of the user for each appliance includes: operation data of each appliance by the user through the mobile terminal and operation data directly by the user to each appliance.
  • the operation data of the user on the electric appliance may be an operation performed by the user on the electric appliance through the APP on the mobile terminal, or may be an operation directly performed by the user on the electric appliance.
  • the training sample data is trained by the model, and the power control model is obtained by: using the influence parameter of the power consumption state of the trainer in the training sample data as an input parameter of the model; and the power supply state of each appliance based on the power of the motorhome is The data is adjusted as an output parameter; the model is trained by input parameters and output parameters to obtain a power control model.
  • the power control model includes a neural network model, and the training sample data is trained by the model, and the power control model is obtained by: determining a neural network according to each appliance's power on/off time period, use time period, using energy consumption, and user operation data.
  • the network structure of the model the number of input nodes of the network, the number of output nodes of the network, the number of hidden layers of the network, the number of nodes on the network, and the initial weight of the network.
  • the user can also actively issue a control command to control the running state of the appliance. For example, in the case of low power, the RV turns off the air conditioner, but the user needs to use it, and can also turn it on again. .
  • the operating state of the first electrical appliance before the operating state of the first electrical appliance is controlled according to the control instruction, obtaining a permission level of the user; determining whether the permission level of the user allows adjustment of the operating state of the first electrical appliance; and if permitted, the first electrical appliance The operating state is adjusted; if it is not allowed, the operating state of the first appliance is not adjusted.
  • User control can be based on their own privilege level.
  • the owner can control the air conditioner, and the guest can not control the air conditioner and can only control the kettle.
  • the privilege level of each user corresponds to the specific content of the operating state adjustment of each appliance, and the privilege and the adjustable appliance may be stored in a list in a server or a control center in the RV.
  • the user's permission can be obtained by the image recognition method.
  • the user with a high level needs to register the record in advance, and then match the newly collected image. If the match is successful, the user is confirmed to be a pre-stored user.
  • determining the power supply state of the target appliance according to the user's permission level. For example, if the guest is in the RV, the car is low in power and the water heater is turned off. If the owner is in the RV, the water heater will not be turned off despite the low battery.
  • the specific target appliance can be powered according to the user's usage. determine.
  • determining the target electrical appliance to be adjusted according to the current power data and the pre-trained power control model includes: determining, by the remote server, the target electrical appliance to be adjusted according to the current power data and the pre-trained power control model; or The server in the RV determines the target appliance to be adjusted according to the current power data and the pre-trained power control model.
  • the control device for adjusting the target electrical appliance may be a remote server or a server in the passenger car, so that the electrical appliances in the passenger car can be intelligently managed regardless of whether the network is connected or disconnected. To ensure the allocation of the optimal power supply algorithm.
  • the technical solution of the embodiment of the present application has the following advantages: First, through a remote cloud server with artificial intelligence algorithm and a module device with an artificial intelligence algorithm, the optimal allocation of the power supply scheme of the RV is realized, and the RV is ensured to be connected to the network. In the case of network disconnection, the allocation of the optimal power supply algorithm can be guaranteed normally. Second, through the use of image and speech recognition technology, quickly bind and identify the identity of the owner, the identity of the guest, and provide different power supply options for different user identities. Third, a set of depth algorithms developed for the RV and the user's own characteristics, to achieve the monitoring, recording and optimization of the power supply program of the home appliance, let the user bid farewell to APP control and remote control. 4. Provide energy monitoring and alarm system. When the power in the RV is insufficient, the navigation function of the nearest charging location will be automatically opened to ensure the normal operation of the RV function.
  • FIG. 2 is a schematic diagram of interaction between a user's internal power equipment and a user according to an embodiment of the present application.
  • the entire system is mainly composed of three parts: a motor home, a cloud server (remote server), and a home appliance inside the motor home.
  • the process server may include an image recognition server and a voice recognition server, and all devices may be connected through a network.
  • the camera installed inside the RV will collect the image information of the user to determine whether the identity of the user is the owner of the RV. If you are entering the RV for the first time, you need to collect and enter the identity information of the owner through the camera. After the user's identity is successfully collected and uploaded to the cloud server, it will be saved as the comparison file to identify the owner after entering the RV.
  • the user When the image information scanned by the camera is successfully matched with the information of the RV owner stored in the background cloud server, the user will be given the highest control right of the RV.
  • the use of the RV by other users requires authorization from the RV owner.
  • the owner authorizes "general authority" the user entering the RV can use the home appliance inside the RV within the range allowed by the power supply system automatically set by the RV, but has no right to dispatch the power distribution of the power supply system. For example, when the energy storage capacity of the RV is 20%, the RV will automatically turn off the household appliances that consume large amounts of electricity (such as air conditioners), send the nearest charging location to the RV owner, and give navigation and positioning lines to ensure the RV.
  • the normal operation of the main internal functions stores energy in time. If the ordinary user is using the air conditioner at the time, the internal power supply system of the car will automatically stop the operation of the air conditioner.
  • the owner of the RV with the highest authority can issue instructions to change the power supply system to ensure the normal operation of the air conditioner.
  • the usage frequency of the home appliance inside the RV will be uploaded to the back-end cloud server, and the neural network algorithm will be adopted in the background cloud server. Analyze and process to obtain the optimal power supply scheme that best suits the user's usage habits.
  • the technical solution of the embodiment of the present application utilizes an artificial neural network algorithm, and is used in a large number of different use environments (including but not limited to one or more of the following: an air conditioner switch time period, an electric water heater use time period, a television viewing period,
  • the user uses the time period of the kitchen appliance in the RV, the daily energy consumption of each household appliance, and the user voice information, etc.)
  • the user collects the time period and energy consumption data of the home appliance in the RV, and selects some state parameters of the RV power supply as the sample.
  • the specific implementation steps are as follows:
  • each of the home appliances will be judged according to the mid of the device and the mac address of the device.
  • Unique identifier For example, the mid-range air conditioning of the RV is 15000, and the corresponding mac is accd0001. Then these two points are used as the identification of the RV air conditioner. When it is confirmed that the air conditioner is internally air-conditioned, the power consumption of the air conditioner during the specific use period will be counted.
  • Specific collection methods include, but are not limited to, operating parameters in a laboratory simulation environment, and collection of operating parameters when an actual user uses a motor home through an Internet of Things technology.
  • the input parameters include, but are not limited to, one or more of the following: an air conditioner switch time period, an electric water heater use time period, a television viewing time period, a user using a kitchen appliance in a RV, and various home appliances. Daily use of energy consumption, user voice information, etc.
  • the input parameters are not only a single parameter, but also a one-dimensional or multi-dimensional array of input parameters composed of features extracted according to a certain rule.
  • the obtained input and output parameter pairs are used as part of training sample data and as part of test sample data.
  • FIG. 3 is a schematic diagram of a neural network algorithm for power distribution of a power supply system of a motor home according to an embodiment of the present application.
  • FIG. 4 is a flowchart of a neural network algorithm according to an embodiment of the present application.
  • the training method of the embodiment of the present application can be adjusted according to the actual network structure and the problems found in the training.
  • One of the methods for the embodiments of the present application is illustrated as follows:
  • the test sample is used to test the network.
  • the test error does not meet the requirements, repeat the above steps to retrain the network; if the test error meets the requirements, the network training test is completed.
  • the electric vehicle electric quantity optimization scheme is automatically adjusted according to the optimized scheme, and the user selects whether to perform the optimized electric energy distribution scheme according to the feedback scheme.
  • the technical solution of the embodiment of the present application can be used as a method for managing a power supply system of a motorhome based on a neural network algorithm, and can implement voice to the user according to the daily usage behavior of the consumer through voice, image recognition, infrared control, and the like.
  • the image and behavioral means are captured and analyzed.
  • the neural network algorithm is used to give the optimal power supply of the RV. It can provide different power supply options for different user identities, which can realize the monitoring, recording and optimization of the home appliance power.
  • the power supply scheme provides an energy monitoring and alarm system to ensure the normal operation of the RV function.
  • the embodiment of the present application provides a power supply control device for a motor home, and the device can be used to implement the power supply control method for the motor home of the embodiment of the present application.
  • FIG. 5 is a schematic diagram of a power supply control device for a motor home according to an embodiment of the present application. As shown in FIG. 5, the device includes:
  • the obtaining unit 10 is configured to obtain current electric quantity data of the RV;
  • a determining unit 20 configured to determine, according to current power data and a pre-trained power control model, a target appliance to be adjusted in a power supply state
  • the control unit 30 is configured to control a power supply state of the target appliance, wherein controlling the power state of the target appliance includes powering the target appliance, powering off the target appliance, or adjusting an operating state of the target appliance.
  • the embodiment is configured to acquire the current electric quantity data of the motor home, and the determining unit 20 is configured to determine the target electric appliance to be adjusted according to the current electric quantity data and the pre-trained electric quantity control model; the control unit 30 is configured to Controlling the power supply state of the target appliance, wherein controlling the power state of the target appliance includes powering the target appliance, powering off the target appliance, or adjusting the operating state of the target appliance, thereby solving the problem that the power management method in the vehicle is not intelligent, thereby achieving The effect of improving the intelligence of power management in the RV.
  • obtaining unit 10, determining unit 20 and control unit 30 may be operated in a computer terminal as part of the device, and the functions implemented by the above modules may be performed by a processor in the computer terminal, and the computer terminal may also It is a smart phone (such as Android phone, iOS phone, etc.), tablet computer, PDA, and mobile Internet devices (MID), PAD and other terminal devices.
  • the RV power supply control device includes a processor and a memory.
  • the above-mentioned acquisition unit, determination unit, control unit, and the like are all stored as a program unit in a memory, and the program unit stored in the memory is executed by the processor to implement a corresponding function.
  • the processor contains a kernel, and the kernel removes the corresponding program unit from the memory.
  • the kernel can be set to one or more, and the intelligence of the power management in the RV can be improved by adjusting the kernel parameters.
  • the memory may include non-persistent memory, random access memory (RAM), and/or non-volatile memory in a computer readable medium, such as read only memory (ROM) or flash memory (flash RAM), the memory including at least one Memory chip.
  • RAM random access memory
  • ROM read only memory
  • flash RAM flash memory
  • the embodiment of the present application provides a storage medium on which a program is stored, and when the program is executed by the processor, the RV power supply control method is implemented.
  • An embodiment of the present application provides a processor, where the processor is configured to run a program, where the program runs to perform the RV power supply control method.
  • An embodiment of the present application provides a device, including a processor, a memory, and a program stored on the memory and operable on the processor.
  • the processor executes the program, the following steps are performed: acquiring current power data of the RV;
  • the power data and the pre-trained power control model determine a target appliance to be adjusted in a power supply state; and control a power state of the target appliance, wherein controlling the power state of the target appliance includes powering the target appliance, powering off the target appliance, or adjusting operation of the target appliance status.
  • the devices in this document can be servers, PCs, PADs, mobile phones, and the like.
  • the present application also provides a computer program product, when executed on a data processing device, adapted to perform a process of initializing the method steps of: obtaining current power data of the motor home; and controlling the model based on the current power data and the pre-trained power control model Determining a target electrical appliance to be adjusted in a power supply state; controlling a power supply state of the target electrical appliance, wherein controlling the power supply state of the target electrical appliance includes powering the target electrical appliance, powering off the target electrical appliance, or adjusting an operating state of the target electrical appliance.
  • embodiments of the present application can be provided as a method, system, or computer program product.
  • the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment in combination of software and hardware.
  • the application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.
  • a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
  • processors CPUs
  • input/output interfaces network interfaces
  • memory volatile and non-volatile memory
  • the memory may include non-persistent memory, random access memory (RAM), and/or non-volatile memory in a computer readable medium, such as read only memory (ROM) or flash memory.
  • RAM random access memory
  • ROM read only memory
  • Memory is an example of a computer readable medium.
  • Computer readable media includes both permanent and non-persistent, removable and non-removable media.
  • Information storage can be implemented by any method or technology.
  • the information can be computer readable instructions, data structures, modules of programs, or other data.
  • Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory. (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disk read only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, Magnetic tape cartridges, magnetic tape storage or other magnetic storage devices or any other non-transportable media can be used to store information that can be accessed by a computing device.
  • computer readable media does not include temporary storage of computer readable media, such as modulated data signals and carrier waves.
  • embodiments of the present application can be provided as a method, system, or computer program product.
  • the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment in combination of software and hardware.
  • the application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.
  • the present application obtains the current electric quantity data of the RV; determines the target electric appliance to be adjusted according to the current electric quantity data and the pre-trained electric quantity control model; and controls the power supply status of the target electric appliance, wherein controlling the power supply status of the target electric appliance includes the target electric appliance Power supply, power off the target electrical appliance or adjust the operating state of the target electrical appliance, solves the problem that the power management method in the motor vehicle is not intelligent, and thus achieves the effect of improving the intelligence of the power management in the passenger car.

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Abstract

本申请公开了一种房车供电控制方法和装置。该方法包括：获取房车当前的电量数据；根据当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器；控制目标电器的供电状态，其中，控制目标电器的供电状态包括对目标电器供电、对目标电器断电或调整目标电器的运行状态。通过本申请，达到了提高房车内用电管理的智能性的效果。

Description

房车供电控制方法和装置 技术领域
本申请涉及房车领域，具体而言，涉及一种房车供电控制方法和装置。
背景技术
目前，汽车进千家万户，已经成为人们日常生活中不可或缺的交通工具之一。房车因内部配备厨房、浴室、空调、电视、卧室等齐全的设备、可移动而备受消费者喜爱。但是，若想这些设备能够最大限度地满足消费者的正常生活需求，供电管理系统是一项极为迫切要解决的问题。
现有的房车的供电方案通常有蓄电池供电、太阳能电池板供电、机械运动存储电能并供电等方式，但是房车由于自身储能有限，如何统一调度并管理房车内部供电系统，并最大限度地满足消费者正常生活用电需求，一直是一个很大的难题。
针对相关技术中房车内用电管理方法不智能的问题，目前尚未提出有效的解决方案。
发明内容
本申请的主要目的在于提供一种房车供电控制方法和装置，以解决房车供电控制问题。
为了实现上述目的，根据本申请的一个方面，提供了一种房车供电控制方法，该方法包括：获取房车当前的电量数据；根据所述当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器；控制所述目标电器的供电状态，其中，控制所述目标电器的供电状态包括对所述目标电器供电、对所述目标电器断电或调整所述目标电器的运行状态。
进一步地，在根据所述当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器之前，所述方法还包括：获取样本数据，其中，所述样本数据至少包括房车内每个电器的耗电数据和用户对每个电器的操作数据；对所述样本数据分为训练样本数据和测试样本数据；将所述训练样本数据进行模型训练，得到电量控制模型；通过所述测试样本数据对所述电量控制模型进行测试，得到测试结果；在所述测试结果符合预设条件的情况下，将所述电量控制模型作为所述预先训练的电量控制模型。
进一步地，获取样本数据包括：获取每个电器的开关机时间段；获取每个电器的使用时间段；获取每个电器的使用能耗；获取每个电器的用户操作数据。
进一步地，获取样本数据包括：根据每个电器的设备身份标识号和物理地址生成对应的标识信息；根据所述标识信息获取每个电器的供电数据。
进一步地，用户对每个电器的操作数据包括：用户通过移动端应用对每个电器的操作数据和用户直接对每个电器的操作数据。
进一步地，将所述训练样本数据进行模型训练，得到电量控制模型包括：将训练样本数据中的对房车电量消耗状态的影响参数作为模型的输入参数；将基于房车电量对每个电器的供电状态的调整数据作为输出参数；通过所述输入参数和所述输出参数进行模型训练，得到所述电量控制模型。
进一步地，所述电量控制模型包括神经网络模型，将所述训练样本数据进行模型训练，得到电量控制模型包括：根据每个电器的开关机时间段、使用时间段、使用能耗和用户操作数据确定所述神经网络模型的网络结构、网络的输入节点数、网络的输出节点数、网络隐层数、网络引节点数和网络初始权值。
进一步地，在控制所述目标电器的供电状态之后，所述方法还包括：接收用户对房车内第一电器的控制指令；根据所述控制指令控制所述第一电器的运行状态。
进一步地，在根据所述控制指令控制所述第一电器的运行状态之前，所述方法还包括：获取所述用户的权限级别；判断所述用户的权限级别是否允许对所述第一电器的运行状态进行调整；在允许的情况下，对所述第一电器的运行状态进行调整；在不允许的情况下，不对所述第一电器的运行状态进行调整。
进一步地，在控制所述目标电器的供电状态之后，所述方法还包括：根据所述用户的权限级别确定所述目标电器的供电状态。
进一步地，在控制所述目标电器的供电状态之后，所述方法还包括：判断房车当前的剩余电量是否小于预设阈值；在房车的剩余电量小于预设阈值的情况下，显示导航信息，其中，所述导航信息为从房车的当前位置到最近的充电地点的导航路线。
进一步地，根据所述当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器包括：远程服务器根据所述当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器；或房车内的服务器根据所述当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器。
为了实现上述目的，根据本申请的另一方面，还提供了一种房车供电控制装置，该装置包括：获取单元，设置为获取房车当前的电量数据；确定单元，设置为根据所 述当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器；控制单元，设置为控制所述目标电器的供电状态，其中，控制所述目标电器的供电状态包括对所述目标电器供电、对所述目标电器断电或调整所述目标电器的运行状态。
为了实现上述目的，根据本申请的另一方面，还提供了一种存储介质，包括存储的程序，其中，在所述程序运行时控制所述存储介质所在设备执行本申请所述的房车供电控制方法。
为了实现上述目的，根据本申请的另一方面，还提供了一种处理器，用于运行程序，其中，所述程序运行时执行本申请所述的房车供电控制方法。
本申请通过获取房车当前的电量数据；根据当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器；控制目标电器的供电状态，其中，控制目标电器的供电状态包括对目标电器供电、对目标电器断电或调整目标电器的运行状态，解决了房车内用电管理方法不智能的问题，进而达到了提高房车内用电管理的智能性的效果。
附图说明
构成本申请的一部分的附图用来提供对本申请的进一步理解，本申请的示意性实施例及其说明用于解释本申请，并不构成对本申请的不当限定。在附图中：
图1是根据本申请实施例的房车供电控制方法的流程图；
图2是根据本申请实施例的房车内部用电设备与用户交互的示意图；
图3是根据本申请实施例的房车供电系统电量分配的神经网络算法的示意图；
图4是根据本申请实施例的神经网络算法的流程图；
图5是根据本申请实施例的房车供电控制装置的示意图。
具体实施方式
需要说明的是，在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互组合。下面将参考附图并结合实施例来详细说明本申请。
为了使本技术领域的人员更好地理解本申请方案，下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本申请一部分的实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都应当属于 本申请保护的范围。
需要说明的是，本申请的说明书和权利要求书及上述附图中的术语“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换，以便这里描述的本申请的实施例。此外，术语“包括”和“具有”以及他们的任何变形，意图在于覆盖不排他的包含，例如，包含了一系列步骤或单元的过程、方法、系统、产品或设备不必限于清楚地列出的那些步骤或单元，而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。
本申请实施例提供了一种房车供电控制方法。
图1是根据本申请实施例的房车供电控制方法的流程图，如图1所示，该方法包括以下步骤：
步骤S102：获取房车当前的电量数据；
步骤S104：根据当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器；
步骤S106：控制目标电器的供电状态，其中，控制目标电器的供电状态包括对目标电器供电、对目标电器断电或调整目标电器的运行状态。
该实施例采用获取房车当前的电量数据；根据当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器；控制目标电器的供电状态，其中，控制目标电器的供电状态包括对目标电器供电、对目标电器断电或调整目标电器的运行状态，解决了房车内用电管理方法不智能的问题，进而达到了提高房车内用电管理的智能性的效果。
在本申请实施例中，房车当前的电量数据可以是房车当前剩余电量，还可以包括房车当前电能消耗数据，预先训练的模型可以是基于该房车的具体情况训练得到的房车内所有用电器的电量消耗模型，包括不同时间段的电量消耗情况，由于不同时间段用户使用的用电器不同，因此，不同时间段房车的耗电情况不同，通过预先训练的模型和当前的电量数据可确定出当前的电量数据的最佳供电策略，包括给哪些电器供电，哪些电器不供电，或者控制一些电器的运行状态，例如，热水器一般在晚上10点左右使用，当前不使用，如果当前房车电量不足可以暂停热水器加热，或者暂停空调使用、调整空调运行模式以节省电量等，确定出需要调整供电状态的目标电器后，可以控制目标电器的供电状态，以使当前的房车电量得到最佳利用，使房车内用电管理更加智能。
可选的，在根据当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器之前，获取样本数据，其中，样本数据至少包括房车内每个电器的耗电数据和用户对每个电器的操作数据；对样本数据分为训练样本数据和测试样本数据；将训练样本数据进行模型训练，得到电量控制模型；通过测试样本数据对电量控制模型进行测试，得到测试结果；在测试结果符合预设条件的情况下，将电量控制模型作为预先训练的电量控制模型。
样本数据可以是基于具体的房车的运行情况进行采集的，例如采集一天的24个时间点的房车内各用电器使用和耗电情况，采集用户对各用电器的操作控制数据等，样本数据可以分为训练样本数据和测试样本数据，基于训练样本数据训练得到模型，然后使用测试数据对模型进行测试，直到满足预设条件才将训练得到的该模型作为预先训练的电量控制模型。预设条件可以是数值误差小于一定的阈值。
可选的，获取样本数据包括：获取每个电器的开关机时间段；获取每个电器的使用时间段；获取每个电器的使用能耗；获取每个电器的用户操作数据。样本数据可以是比较全面的电器使用数据，例如，开关机时间点，使用过程中的耗能数据，用户使用该用电器的操作数据等，一般情况下，获取到的数据越多越全面，越有利于建立准确的模型。
可选的，获取样本数据包括：根据每个电器的设备身份标识号和物理地址生成对应的标识信息；根据标识信息获取每个电器的供电数据。
为了对每个电器区分，可以为每个电器生成唯一的标识信息，标识信息的生成可以基于每个电器设备的身份标识号(mid)和物理地址。
可选的，用户对每个电器的操作数据包括：用户通过移动端应用对每个电器的操作数据和用户直接对每个电器的操作数据。用户对电器的操作数据可以是用户通过移动终端上的APP对电器进行的操作，也可以是用户直接对用电器进行的操作。
可选的，将训练样本数据进行模型训练，得到电量控制模型包括：将训练样本数据中的对房车电量消耗状态的影响参数作为模型的输入参数；将基于房车电量对每个电器的供电状态的调整数据作为输出参数；通过输入参数和输出参数进行模型训练，得到电量控制模型。
可选的，电量控制模型包括神经网络模型，将训练样本数据进行模型训练，得到电量控制模型包括：根据每个电器的开关机时间段、使用时间段、使用能耗和用户操作数据确定神经网络模型的网络结构、网络的输入节点数、网络的输出节点数、网络隐层数、网络引节点数和网络初始权值。
可选的，在控制目标电器的供电状态之后，接收用户对房车内第一电器的控制指 令；根据控制指令控制第一电器的运行状态。除了根据预先训练好的模型控制目标电器的供电状态，还可以用户主动发出控制指令，控制电器的运行状态，例如，电量低的情况下，房车关闭了空调，但用户需要使用，也可以再打开。
可选的，在根据控制指令控制第一电器的运行状态之前，获取用户的权限级别；判断用户的权限级别是否允许对第一电器的运行状态进行调整；在允许的情况下，对第一电器的运行状态进行调整；在不允许的情况下，不对第一电器的运行状态进行调整。
用户控制可以基于自己的权限级别，例如，主人可以控制空调，而客人不可以控制空调，仅可以控制烧水壶。每个用户的权限级别对应每个电器的运行状态调整的具体内容，该权限和可调整的电器可以是以列表形式存储在房车内的服务器或者控制中心中。识别用户的权限可以是以图像识别的方法获取当前用户的权限，级别高的用户需要预先注册记录，然后与新采集到的图像匹配，匹配成功的情况下确认该用户就是预存的用户。
可选的，在控制目标电器的供电状态之后，根据用户的权限级别确定目标电器的供电状态。例如，客人在房车中，此时房车电量低关闭热水器，而如果主人在房车中，此时尽管电量低，仍不关闭热水器，具体的目标电器在不同剩余电量下的供电状态可以根据用户使用习惯确定。
可选的，在控制目标电器的供电状态之后，判断房车当前的剩余电量是否小于预设阈值；在房车的剩余电量小于预设阈值的情况下，显示导航信息，其中，导航信息为从房车的当前位置到最近的充电地点的导航路线。
如果房车内剩余电量过低，可以显示导航信息，引导用户尽快开到最近的充电地点充电。
可选的，根据当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器包括：远程服务器根据当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器；或房车内的服务器根据当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器。
根据当前的电量数据和模型确定对目标电器进行调整的控制设备可以是远程服务器，也可以是房车内的服务器，这样无论在联网还是在断网的情况下，都能智能管理房车内的用电器，保证最优供电算法的分配。
本申请实施例的技术方案具有以下优点：一、通过远程的带人工智能算法的云端服务器和进程的带人工智能的算法的模块装置，实现对房车供电方案的最优化分配，确保房车在联网和断网情况下都能够正常保证最优供电算法的分配。二、通过图像、 语音识别技术的运用，快速绑定和识别主人身份、客人身份，针对不同的用户身份提供不同的供电选择方案。三、针对房车和用户自身特点研发的一整套深度算法，实现对家电电量的监控、记录和最优化供电方案给出，让用户告别APP控制和遥控器控制。四、提供能量监控报警系统，在房车内电量不足时，会自动开启定位查询最近充电地点的导航功能，确保房车功能的正常运行。
本申请实施例还提供了一种优选实施方式，下面结合该优选实施方式对本申请实施例的技术方案进行说明。
图2是根据本申请实施例的房车内部用电设备与用户交互的示意图，如图2所示，整个系统主要由三大部分组成：房车、云端服务器(远程服务器)、房车内部的家电设备。进程服务器可以包括图像识别服务器和语音识别服务器，所有设备之间可以通过网络连接。
具体实施方法如下：
1、用户进入房车后，房车内部安装的摄像头会采集用户的图像信息，判断用户的身份是否房车的主人。如果是第一次进入房车，需要先经过摄像头采集并录入主人的身份信息。用户的主人身份采集成功并上传至云服务器之后，会保存下来，作为下次进入房车之后识别主人身份的比对文件。
2、当摄像头扫描到的用户图像信息与后台云服务器存储的房车主人信息匹配成功后，就会给用户开启房车的最高控制权限。其他的用户对房车的使用需要经过房车主人的授权。主人授权为“普通权限”时，进入房车的用户可以在房车自动设定的供电系统允许的范围内使用房车内部的家电产品，但是无权调度供电系统的电量分配。比如：当房车储能电量为20％时，房车会自动关闭耗电量大的家电产品(如：空调等)，向房车主人发出附近最近的充电地点，并给出导航定位线路，以确保房车内部主要功能的正常运转及时储备电能。如果普通用户当时正在使用空调，此时房车内部供电系统会自动停止空调的运行。而拥用最高权限的房车主人可以发出指令，改变供电系统方案，确保空调的正常运行。
3、当房车主人在日常生活过程中，房车内部的家电设备的使用频率、用户对家电的使用时间、使用喜好等行为习惯都会被上传至后台云服务器，在后台云服务器中会通过神经网络算法进行分析处理，得出最符合用户使用习惯的最优电源供电方案。
本申请实施例的技术方案利用人工神经网络算法，通过对大量不同使用环境下(包括但不限于如下的一种或多种：空调开关机时间段、电热水器使用时间段、观看电视时间段、用户使用房车中厨房电器时间段、各个家电产品的日常使用能耗、用户语音信息等综合方式等)用户使用房车中家电产品时间段和能耗数据汇总收集，选取若干 房车供电特征状态参数作为样本数据，对神经网络进行学习和训练，通过调整网络结构及网络节点间的权值，使神经网络拟合用户使用房车内家电产品能耗动态指标参数和房车供电系统分配方案之间的关系，最终使神经网络能准确拟合出房车供电系统分配方案的运行参数与用户使用房车家电产品能耗间的对应关系。具体实施步骤如下：
1、数据搜集：
搜集用户在使用不同家电产品能耗环境下的房车电量的运行状态参数及对应的确定房车供电分配方案的信息情况。由于不同的家电产品耗电量并不相同，因此，在搜集房车内部家电产品的耗电量时，采用具体的每一种家电产品会根据设备的mid和对应该设备的mac地址作为判定该设备的唯一标识。比如：房车内部空调的mid为15000，对应的mac为accd0001，那么通过这两点就作为房车空调的标识。确认是房车内部空调时，就将统计该空调的在具体使用时间段的耗电量，之后这个耗电时间点、耗电量多少都会被记录下来，最后上传至云端服务器作为统计分析的数据来源。具体搜集方式包括但不限于在实验室模拟环境下的运行参数、通过物联网技术搜集实际用户使用房车时的运行参数等方式。
2、样本数据选择
通过对数据的分析和结合专家经验知识，选取对房车电量消耗状态有影响的参数作为输入参数，将确定供电系统分配方案的信息状态作为输出参数。本申请实施例中，输入参数包括但不限于如下的一种或多种：空调开关机时间段、电热水器使用时间段、观看电视时间段、用户使用房车中厨房电器时间段、各个家电产品的日常使用能耗、用户语音信息等。输入参数不仅为单一参数，也包括按一定规律提取特征组成的输入参数一维或多维数组。
将得到的输入、输出参数对，一部分用作训练本样数据，一部分用作测试样本数据。
3、网络结构设计
根据空调开关机时间段、电热水器使用时间段、观看电视时间段、用户使用房车中厨房电器时间段、各个家电产品的日常使用能耗、用户语音信息等房车耗电量影响的数据特性及其所蕴含的规律分析，可初步确定网络的基本结构、网络的输入、输出节点数、网络隐层数、隐节点数、网络初始权值等。图3是根据本申请实施例的房车供电系统电量分配的神经网络算法的示意图。
4、网络训练与测试
网络设计完成后，需用训练样本数据，对网络进行训练，图4是根据本申请实施 例的神经网络算法的流程图。
本申请实施例的训练方法可根据实际的网络结构及训练中发现的问题进行调整。针对本申请实施例的其中一种方法举例说明如下：
导入输入数据x，根据激活函数、初始化的权值及偏置计算出网络的实际输出a(x)，即a(x)＝1/(1+e-z),其中Z＝Wk*x+bl
判断网络的期望输出y(x)与实际输出a(x)是否满足输出精度要求即：
‖y(x)-a(x)‖<∈，∈为目标最小误差
网络训练完成后，再用测试样本正向测试网络。当测试误差不满足要求时，则重复以上步骤，重新训练网络；若测试误差满足要求，则网络训练测试完成。之后将根据优化后的方案自动调整房车电量优化方案，用户根据反馈的方案选择是否执行优化后的电量分配方案。
本申请实施例的技术方案可以作为一种基于神经网络算法的房车电源供电系统管理方法，能够根据消费者的日常使用行为习惯，通过语音、图像识别、红外控制等技术手段，实现对用户语音、图像和行为手段的捕捉并分析，通过神经网络算法给出房车内部电源供给最优方案，能够针对不同的用户身份提供不同的供电选择方案，可以实现对家电电量的监控、记录和给出最优化供电方案，提供能量监控报警系统，确保房车功能的正常运行。
需要说明的是，在附图的流程图示出的步骤可以在诸如一组计算机可执行指令的计算机系统中执行，并且，虽然在流程图中示出了逻辑顺序，但是在某些情况下，可以以不同于此处的顺序执行所示出或描述的步骤。
本申请实施例提供了一种房车供电控制装置，该装置可以用于执行本申请实施例的房车供电控制方法。
图5是根据本申请实施例的房车供电控制装置的示意图，如图5所示，该装置包括：
获取单元10，用于获取房车当前的电量数据；
确定单元20，用于根据当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器；
控制单元30，用于控制目标电器的供电状态，其中，控制目标电器的供电状态包括对目标电器供电、对目标电器断电或调整目标电器的运行状态。
该实施例采用获取单元10，用于获取房车当前的电量数据；确定单元20，用于根据当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器；控制单元30，用于控制目标电器的供电状态，其中，控制目标电器的供电状态包括对目标电器供电、对目标电器断电或调整目标电器的运行状态，从而解决了房车内用电管理方法不智能的问题，进而达到了提高房车内用电管理的智能性的效果。
此处需要说明的是，上述获取单元10、确定单元20和控制单元30可以作为装置的一部分运行在计算机终端中，可以通过计算机终端中的处理器来执行上述模块实现的功能，计算机终端也可以是智能手机(如Android手机、iOS手机等)、平板电脑、掌上电脑以及移动互联网设备(Mobile Internet Devices，MID)、PAD等终端设备。
房车供电控制装置包括处理器和存储器，上述获取单元、确定单元、控制单元等均作为程序单元存储在存储器中，由处理器执行存储在存储器中的上述程序单元来实现相应的功能。
处理器中包含内核，由内核去存储器中调取相应的程序单元。内核可以设置一个或以上，通过调整内核参数来提高房车内用电管理的智能性。
存储器可能包括计算机可读介质中的非永久性存储器，随机存取存储器(RAM)和/或非易失性内存等形式，如只读存储器(ROM)或闪存(flash RAM)，存储器包括至少一个存储芯片。
本申请实施例提供了一种存储介质，其上存储有程序，该程序被处理器执行时实现所述房车供电控制方法。
本申请实施例提供了一种处理器，所述处理器用于运行程序，其中，所述程序运行时执行所述房车供电控制方法。
本申请实施例提供了一种设备，设备包括处理器、存储器及存储在存储器上并可在处理器上运行的程序，处理器执行程序时实现以下步骤：获取房车当前的电量数据；根据当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器；控制目标电器的供电状态，其中，控制目标电器的供电状态包括对目标电器供电、对目标电器断电或调整目标电器的运行状态。本文中的设备可以是服务器、PC、PAD、手机等。
本申请还提供了一种计算机程序产品，当在数据处理设备上执行时，适于执行初始化有如下方法步骤的程序：获取房车当前的电量数据；根据当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器；控制目标电器的供电状态，其中，控制目标电器的供电状态包括对目标电器供电、对目标电器断电或调整目标电器的运行状态。
本领域内的技术人员应明白，本申请的实施例可提供为方法、系统、或计算机程序产品。因此，本申请可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本申请是参照根据本申请实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
在一个典型的配置中，计算设备包括一个或多个处理器(CPU)、输入/输出接口、网络接口和内存。
存储器可能包括计算机可读介质中的非永久性存储器，随机存取存储器(RAM)和/或非易失性内存等形式，如只读存储器(ROM)或闪存(flash RAM)。存储器是计算机可读介质的示例。
计算机可读介质包括永久性和非永久性、可移动和非可移动媒体可以由任何方法或技术来实现信息存储。信息可以是计算机可读指令、数据结构、程序的模块或其他数据。计算机的存储介质的例子包括，但不限于相变内存(PRAM)、静态随机存取存储器(SRAM)、动态随机存取存储器(DRAM)、其他类型的随机存取存储器(RAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、快闪记忆体或其他内存技术、只读光盘只读存储器(CD-ROM)、数字多功能光盘(DVD)或其他光学存储、磁盒式磁带，磁带磁磁盘存储或其他磁性存储设备或任何其他非传输介质，可用于存 储可以被计算设备访问的信息。按照本文中的界定，计算机可读介质不包括暂存电脑可读媒体(transitory media)，如调制的数据信号和载波。
还需要说明的是，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、商品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、商品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括要素的过程、方法、商品或者设备中还存在另外的相同要素。
本领域技术人员应明白，本申请的实施例可提供为方法、系统或计算机程序产品。因此，本申请可采用完全硬件实施例、完全软件实施例或结合软件和硬件方面的实施例的形式。而且，本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
以上仅为本申请的实施例而已，并不用于限制本申请。对于本领域技术人员来说，本申请可以有各种更改和变化。凡在本申请的精神和原理之内所作的任何修改、等同替换、改进等，均应包含在本申请的权利要求范围之内。
工业实用性
本申请通过获取房车当前的电量数据；根据当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器；控制目标电器的供电状态，其中，控制目标电器的供电状态包括对目标电器供电、对目标电器断电或调整目标电器的运行状态，解决了房车内用电管理方法不智能的问题，进而达到了提高房车内用电管理的智能性的效果。

Claims (15)

  1. 一种房车供电控制方法，包括：
    获取房车当前的电量数据；
    根据所述当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器；
    控制所述目标电器的供电状态，其中，控制所述目标电器的供电状态包括对所述目标电器供电、对所述目标电器断电或调整所述目标电器的运行状态。
  2. 根据权利要求1所述的方法，其中，在根据所述当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器之前，所述方法还包括：
    获取样本数据，其中，所述样本数据至少包括房车内每个电器的耗电数据和用户对每个电器的操作数据；
    对所述样本数据分为训练样本数据和测试样本数据；
    将所述训练样本数据进行模型训练，得到电量控制模型；
    通过所述测试样本数据对所述电量控制模型进行测试，得到测试结果；
    在所述测试结果符合预设条件的情况下，将所述电量控制模型作为所述预先训练的电量控制模型。
  3. 根据权利要求2所述的方法，其中，获取样本数据包括：
    获取每个电器的开关机时间段；
    获取每个电器的使用时间段；
    获取每个电器的使用能耗；
    获取每个电器的用户操作数据。
  4. 根据权利要求3所述的方法，其中，获取样本数据包括：
    根据每个电器的设备身份标识号和物理地址生成对应的标识信息；
    根据所述标识信息获取每个电器的供电数据。
  5. 根据权利要求2所述的方法，其中，用户对每个电器的操作数据包括：
    用户通过移动端应用对每个电器的操作数据和用户直接对每个电器的操作数据。
  6. 根据权利要求1所述的方法，其中，将所述训练样本数据进行模型训练，得到电量控制模型包括：
    将训练样本数据中的对房车电量消耗状态的影响参数作为模型的输入参数；
    将基于房车电量对每个电器的供电状态的调整数据作为输出参数；
    通过所述输入参数和所述输出参数进行模型训练，得到所述电量控制模型。
  7. 根据权利要求6所述的方法，其中，所述电量控制模型包括神经网络模型，将所述训练样本数据进行模型训练，得到电量控制模型包括：
    根据每个电器的开关机时间段、使用时间段、使用能耗和用户操作数据确定所述神经网络模型的网络结构、网络的输入节点数、网络的输出节点数、网络隐层数、网络引节点数和网络初始权值。
  8. 根据权利要求2所述的方法，其中，在控制所述目标电器的供电状态之后，所述方法还包括：
    接收用户对房车内第一电器的控制指令；
    根据所述控制指令控制所述第一电器的运行状态。
  9. 根据权利要求8所述的方法，其中，在根据所述控制指令控制所述第一电器的运行状态之前，所述方法还包括：
    获取所述用户的权限级别；
    判断所述用户的权限级别是否允许对所述第一电器的运行状态进行调整；
    在允许的情况下，对所述第一电器的运行状态进行调整；
    在不允许的情况下，不对所述第一电器的运行状态进行调整。
  10. 根据权利要求9所述的方法，其中，在控制所述目标电器的供电状态之后，所述方法还包括：
    根据所述用户的权限级别确定所述目标电器的供电状态。
  11. 根据权利要求1所述的方法，其中，在控制所述目标电器的供电状态之后，所述方法还包括：
    判断房车当前的剩余电量是否小于预设阈值；
    在房车的剩余电量小于预设阈值的情况下，显示导航信息，其中，所述导航 信息为从房车的当前位置到最近的充电地点的导航路线。
  12. 根据权利要求1所述的方法，其中，根据所述当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器包括：
    远程服务器根据所述当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器；或
    房车内的服务器根据所述当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器。
  13. 一种房车供电控制设备，包括：
    获取单元，设置为获取房车当前的电量数据；
    确定单元，设置为根据所述当前的电量数据和预先训练的电量控制模型确定待调整供电状态的目标电器；
    控制单元，设置为控制所述目标电器的供电状态，其中，控制所述目标电器的供电状态包括对所述目标电器供电、对所述目标电器断电或调整所述目标电器的运行状态。
  14. 一种存储介质，所述存储介质包括存储的程序，其中，在所述程序运行时控制所述存储介质所在设备执行权利要求1至12中任意一项所述的房车供电控制方法。
  15. 一种处理器，所述处理器用于运行程序，其中，所述程序运行时执行权利要求1至12中任意一项所述的房车供电控制方法。
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